A Generalized Framework for Concentric Tube Robot Design Using Gradient-Based Optimization

Concentric tube robots (CTRs) show particular promise for minimally invasive surgery due to their inherent com- pliance and ability to navigate in constrained environments. Due to variations in anatomy among patients and variations in task requirements among procedures, it is necessary to customize the design of these robots on a patient- or population-specific basis. However, the complex kinematics and large design space make the design problem challenging. In this article, we propose a com- putational framework that can efficiently optimize a robot design and a motion plan to enable safe navigation through the patient’s anatomy. The current framework is the first fully gradient-based method for CTR design optimization and motion planning, en- abling an efficient and scalable solution for simultaneously opti- mizing continuous variables, even across multiple anatomies. The framework is demonstrated using two clinical examples, laryn- goscopy and heart biopsy, where the optimization problems are solved for a single patient and across multiple patients, respectively.